{"id":9008,"date":"2024-11-19T05:30:57","date_gmt":"2024-11-19T13:30:57","guid":{"rendered":"https:\/\/devblogs.microsoft.com\/cosmosdb\/?p=9008"},"modified":"2024-11-13T06:55:28","modified_gmt":"2024-11-13T14:55:28","slug":"autoscale-in-public-preview-for-vcore-based-azure-cosmos-db-for-mongodb","status":"publish","type":"post","link":"https:\/\/devblogs.microsoft.com\/cosmosdb\/autoscale-in-public-preview-for-vcore-based-azure-cosmos-db-for-mongodb\/","title":{"rendered":"Autoscale in public preview for vCore-based Azure Cosmos DB for MongoDB"},"content":{"rendered":"

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Managing workloads with unpredictable spikes can be a real challenge, especially when it comes to ensuring your database can handle sudden surges in traffic. Often, this leads to overprovisioning resources to play it safe, resulting in higher costs and wasted capacity. But what if there was a better way? We’re excited to introduce Autoscale for vCore-based Azure Cosmos DB for MongoDB<\/a>, a feature designed to take the guesswork out of scaling. With Autoscale, your database seamlessly adjusts to meet peak demand, eliminating the need for overprovisioning, cutting costs, and maintaining peak performance effortlessly.<\/p>\n

What is Autoscale?<\/span><\/strong><\/h2>\n

The vCore-based MongoDB in Azure Cosmos DB<\/a> now includes a new cluster tier called Autoscale, designed to provide clusters that automatically scale up or down based on application usage.<\/p>\n

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Unlike other managed MongoDB solutions that suffer from significant delays when adjusting capacity\u2014where scaling up can take hours and scaling down may exceed 24 hours\u2014these limitations often result in missed peak usage windows and compromised performance. Autoscale ensures real-time responsiveness. This means your database adjusts dynamically as workload demands shift, so you aren\u2019t stuck paying for larger machines unnecessarily. This approach offers few key benefits:<\/p>\n

Instant Scale<\/strong><\/span><\/h3>\n

Autoscale ensures your database scales instantly to handle peak demand without downtime or performance loss, adapting seamlessly to sudden or periodic workload spikes.<\/p>\n

Budget-Friendly<\/strong><\/span><\/h3>\n

Avoid overprovisioning and reduce expenses with Autoscale\u2019s pay-as-you-use model, maximizing resource utilization and cutting unnecessary costs.<\/p>\n

Predictable Pricing<\/strong><\/span><\/h3>\n

With core-based pricing, Autoscale provides transparent and manageable costs, making it easier to budget and plan for database operations.<\/p>\n

Pricing model<\/span><\/strong><\/h2>\n

Autoscale follows a core-based pricing model, charging based on the higher of CPU or memory usage in the last hour, compared to a 35% threshold. If utilization is below 35%, the minimum price applies; above 35%, the maximum price applies. Autoscale clusters carry a 50% premium over the base tier, with costs billed hourly, ensuring you only pay for what you use.<\/p>\n

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The chart above illustrates an application that experienced usage spikes for 10% of its total runtime. In this scenario, a user with a regularly overprovisioned M200 cluster would have paid $1,185.24. However, with the M200-Autoscale cluster, the cost would drop to $968.41, resulting in a savings of 18.29% while still giving you instant performance, so your users are happy.<\/p>\n

Conclusion<\/span><\/strong><\/h2>\n

In conclusion, Autoscale for vCore-based Azure Cosmos DB for MongoDB offers a powerful, cost-efficient solution that automatically adjusts to your workload demands. With its flexible pricing model and instant scalability, you get the performance users need instantly while avoiding overprovisioning by paying for only what you use.<\/p>\n

Leave a review<\/strong><\/span><\/h2>\n

Tell us about your Azure Cosmos DB experience! Leave a review on PeerSpot and we\u2019ll gift you $50. Get started here.<\/a><\/p>\n

About Azure Cosmos DB<\/h2>\n

Azure Cosmos DB is a fully managed and serverless distributed database for modern app development, with SLA-backed speed and availability, automatic and instant scalability, and support for open-source PostgreSQL, MongoDB, and Apache Cassandra.\u00a0Try Azure Cosmos DB for free here.<\/a>\u00a0To stay in the loop on Azure Cosmos DB updates, follow us on\u00a0X<\/a>,\u00a0YouTube<\/a>, and\u00a0LinkedIn<\/a>.<\/p>\n","protected":false},"excerpt":{"rendered":"

Managing workloads with unpredictable spikes can be a real challenge, especially when it comes to ensuring your database can handle sudden surges in traffic. Often, this leads to overprovisioning resources to play it safe, resulting in higher costs and wasted capacity. But what if there was a better way? We’re excited to introduce Autoscale for […]<\/p>\n","protected":false},"author":125125,"featured_media":9011,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[15],"tags":[],"class_list":["post-9008","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-mongodb-api"],"acf":[],"blog_post_summary":"

Managing workloads with unpredictable spikes can be a real challenge, especially when it comes to ensuring your database can handle sudden surges in traffic. Often, this leads to overprovisioning resources to play it safe, resulting in higher costs and wasted capacity. But what if there was a better way? We’re excited to introduce Autoscale for […]<\/p>\n","_links":{"self":[{"href":"https:\/\/devblogs.microsoft.com\/cosmosdb\/wp-json\/wp\/v2\/posts\/9008","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/devblogs.microsoft.com\/cosmosdb\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/devblogs.microsoft.com\/cosmosdb\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/devblogs.microsoft.com\/cosmosdb\/wp-json\/wp\/v2\/users\/125125"}],"replies":[{"embeddable":true,"href":"https:\/\/devblogs.microsoft.com\/cosmosdb\/wp-json\/wp\/v2\/comments?post=9008"}],"version-history":[{"count":0,"href":"https:\/\/devblogs.microsoft.com\/cosmosdb\/wp-json\/wp\/v2\/posts\/9008\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/devblogs.microsoft.com\/cosmosdb\/wp-json\/wp\/v2\/media\/9011"}],"wp:attachment":[{"href":"https:\/\/devblogs.microsoft.com\/cosmosdb\/wp-json\/wp\/v2\/media?parent=9008"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/devblogs.microsoft.com\/cosmosdb\/wp-json\/wp\/v2\/categories?post=9008"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/devblogs.microsoft.com\/cosmosdb\/wp-json\/wp\/v2\/tags?post=9008"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}